Overview

Dataset statistics

Number of variables36
Number of observations471
Missing cells25
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.6 KiB
Average record size in memory288.3 B

Variable types

CAT20
NUM16

Warnings

Bes2 has constant value "471" Constant
TempIL is highly correlated with TempGLHigh correlation
TempGL is highly correlated with TempILHigh correlation
SpatIL is highly correlated with SpatGLHigh correlation
SpatGL is highly correlated with SpatILHigh correlation
Lich2 is highly correlated with Lich1High correlation
Lich1 is highly correlated with Lich2High correlation
TempIL is highly correlated with TempGLHigh correlation
TempGL is highly correlated with TempILHigh correlation
Fstf has 25 (5.3%) missing values Missing
df_index has unique values Unique
TempDist has 396 (84.1%) zeros Zeros
SpatDist has 378 (80.3%) zeros Zeros
UArt1 has 13 (2.8%) zeros Zeros
AUrs1 has 437 (92.8%) zeros Zeros

Reproduction

Analysis started2020-10-29 21:41:43.240796
Analysis finished2020-10-29 21:42:51.747547
Duration1 minute and 8.51 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct471
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean976.4161359
Minimum2
Maximum1852
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:42:52.216941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile128.5
Q1544.5
median992
Q31415.5
95-th percentile1754
Maximum1852
Range1850
Interquartile range (IQR)871

Descriptive statistics

Standard deviation521.3039348
Coefficient of variation (CV)0.5338952478
Kurtosis-1.110627537
Mean976.4161359
Median Absolute Deviation (MAD)430
Skewness-0.1252774804
Sum459892
Variance271757.7924
MonotocityStrictly increasing
2020-10-29T22:42:52.416450image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
102310.2%
 
34210.2%
 
32210.2%
 
134910.2%
 
32810.2%
 
33010.2%
 
33110.2%
 
135610.2%
 
135810.2%
 
135910.2%
 
Other values (461)46197.9%
 
ValueCountFrequency (%) 
210.2%
 
510.2%
 
810.2%
 
910.2%
 
1010.2%
 
ValueCountFrequency (%) 
185210.2%
 
183710.2%
 
183510.2%
 
183410.2%
 
183310.2%
 

TempMax
Real number (ℝ≥0)

Distinct169
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.9808917
Minimum9
Maximum1323
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:42:52.604080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile24
Q179.5
median150
Q3286.5
95-th percentile661.5
Maximum1323
Range1314
Interquartile range (IQR)207

Descriptive statistics

Standard deviation212.7688128
Coefficient of variation (CV)0.9672149757
Kurtosis6.452013531
Mean219.9808917
Median Absolute Deviation (MAD)90
Skewness2.214838711
Sum103611
Variance45270.56772
MonotocityNot monotonic
2020-10-29T22:42:52.773041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
129112.3%
 
8191.9%
 
3091.9%
 
7891.9%
 
13581.7%
 
12371.5%
 
8771.5%
 
11771.5%
 
7571.5%
 
4271.5%
 
Other values (159)39082.8%
 
ValueCountFrequency (%) 
930.6%
 
1230.6%
 
1520.4%
 
1861.3%
 
2151.1%
 
ValueCountFrequency (%) 
132320.4%
 
125720.4%
 
119410.2%
 
102910.2%
 
96010.2%
 

TempAvg
Real number (ℝ≥0)

Distinct174
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.9044586
Minimum4
Maximum1326
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:42:53.113013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q130
median61
Q399
95-th percentile226.5
Maximum1326
Range1322
Interquartile range (IQR)69

Descriptive statistics

Standard deviation115.1059152
Coefficient of variation (CV)1.339929464
Kurtosis59.31657529
Mean85.9044586
Median Absolute Deviation (MAD)34
Skewness6.555039442
Sum40461
Variance13249.3717
MonotocityNot monotonic
2020-10-29T22:42:53.287919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1871.5%
 
871.5%
 
1171.5%
 
8971.5%
 
5671.5%
 
2671.5%
 
9971.5%
 
2471.5%
 
4471.5%
 
2371.5%
 
Other values (164)40185.1%
 
ValueCountFrequency (%) 
410.2%
 
510.2%
 
630.6%
 
751.1%
 
871.5%
 
ValueCountFrequency (%) 
132610.2%
 
126010.2%
 
95510.2%
 
70310.2%
 
57510.2%
 

SpatMax
Real number (ℝ≥0)

Distinct428
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14241.98089
Minimum832
Maximum219082
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:42:53.466448image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum832
5-th percentile2169.5
Q15616.5
median9574
Q317188
95-th percentile37023.5
Maximum219082
Range218250
Interquartile range (IQR)11571.5

Descriptive statistics

Standard deviation19325.269
Coefficient of variation (CV)1.356922829
Kurtosis59.79710056
Mean14241.98089
Median Absolute Deviation (MAD)5074
Skewness6.758608342
Sum6707973
Variance373466021.9
MonotocityNot monotonic
2020-10-29T22:42:53.615622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
602530.6%
 
991730.6%
 
957430.6%
 
4239330.6%
 
662130.6%
 
1563920.4%
 
416820.4%
 
1316320.4%
 
1856920.4%
 
474720.4%
 
Other values (418)44694.7%
 
ValueCountFrequency (%) 
83210.2%
 
111010.2%
 
119410.2%
 
120610.2%
 
128010.2%
 
ValueCountFrequency (%) 
21908210.2%
 
18973020.4%
 
15323710.2%
 
7072610.2%
 
6494310.2%
 

SpatAvg
Real number (ℝ≥0)

Distinct437
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4005.225053
Minimum583
Maximum13744
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:42:53.768206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum583
5-th percentile1034.5
Q12050
median3355
Q35605
95-th percentile8890
Maximum13744
Range13161
Interquartile range (IQR)3555

Descriptive statistics

Standard deviation2525.928992
Coefficient of variation (CV)0.630658442
Kurtosis0.7791238899
Mean4005.225053
Median Absolute Deviation (MAD)1616
Skewness1.020843813
Sum1886461
Variance6380317.273
MonotocityNot monotonic
2020-10-29T22:42:56.481453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
560630.6%
 
402230.6%
 
242230.6%
 
126420.4%
 
183120.4%
 
785120.4%
 
951120.4%
 
349420.4%
 
828520.4%
 
156420.4%
 
Other values (427)44895.1%
 
ValueCountFrequency (%) 
58310.2%
 
62510.2%
 
64310.2%
 
66010.2%
 
67010.2%
 
ValueCountFrequency (%) 
1374410.2%
 
1248010.2%
 
1236310.2%
 
1228810.2%
 
1217410.2%
 

TempDist
Real number (ℝ≥0)

ZEROS

Distinct25
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.097664544
Minimum0
Maximum24
Zeros396
Zeros (%)84.1%
Memory size3.7 KiB
2020-10-29T22:42:56.626986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17.5
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.531631946
Coefficient of variation (CV)2.637043164
Kurtosis6.106655339
Mean2.097664544
Median Absolute Deviation (MAD)0
Skewness2.687304112
Sum988
Variance30.59895198
MonotocityNot monotonic
2020-10-29T22:42:56.752952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
039684.1%
 
1871.5%
 
671.5%
 
561.3%
 
1761.3%
 
2461.3%
 
1251.1%
 
940.8%
 
1630.6%
 
230.6%
 
Other values (15)285.9%
 
ValueCountFrequency (%) 
039684.1%
 
110.2%
 
230.6%
 
310.2%
 
410.2%
 
ValueCountFrequency (%) 
2461.3%
 
2330.6%
 
2220.4%
 
2130.6%
 
2010.2%
 

SpatDist
Real number (ℝ≥0)

ZEROS

Distinct80
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.7154989
Minimum0
Maximum2000
Zeros378
Zeros (%)80.3%
Memory size3.7 KiB
2020-10-29T22:42:56.894239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile722
Maximum2000
Range2000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation306.4723023
Coefficient of variation (CV)2.899029049
Kurtosis14.88397032
Mean105.7154989
Median Absolute Deviation (MAD)0
Skewness3.737164569
Sum49792
Variance93925.27208
MonotocityNot monotonic
2020-10-29T22:42:57.039853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
037880.3%
 
25040.8%
 
29030.6%
 
125030.6%
 
5030.6%
 
71820.4%
 
11220.4%
 
25220.4%
 
320.4%
 
21020.4%
 
Other values (70)7014.9%
 
ValueCountFrequency (%) 
037880.3%
 
320.4%
 
2110.2%
 
2210.2%
 
5030.6%
 
ValueCountFrequency (%) 
200010.2%
 
194910.2%
 
176610.2%
 
171310.2%
 
170310.2%
 

Coverage
Real number (ℝ≥0)

Distinct78
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.02760085
Minimum2
Maximum100
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:42:57.217453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile11
Q123
median35
Q347
95-th percentile70
Maximum100
Range98
Interquartile range (IQR)24

Descriptive statistics

Standard deviation18.29153049
Coefficient of variation (CV)0.4939971824
Kurtosis0.2306551822
Mean37.02760085
Median Absolute Deviation (MAD)12
Skewness0.6356840901
Sum17440
Variance334.5800876
MonotocityNot monotonic
2020-10-29T22:42:57.400790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
40173.6%
 
18153.2%
 
30153.2%
 
37143.0%
 
42132.8%
 
25132.8%
 
35132.8%
 
38122.5%
 
31122.5%
 
16112.3%
 
Other values (68)33671.3%
 
ValueCountFrequency (%) 
210.2%
 
320.4%
 
520.4%
 
640.8%
 
720.4%
 
ValueCountFrequency (%) 
10020.4%
 
9010.2%
 
8840.8%
 
8610.2%
 
8510.2%
 

TempGL
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
3
396 
5
75 
ValueCountFrequency (%) 
339684.1%
 
57515.9%
 
2020-10-29T22:42:57.911401image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:42:58.544058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:01.291422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

SpatGL
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2
378 
3
93 
ValueCountFrequency (%) 
237880.3%
 
39319.7%
 
2020-10-29T22:43:01.397578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:01.472601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:06.659959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

TempIL
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
4
217 
5
179 
-1
75 
ValueCountFrequency (%) 
421746.1%
 
517938.0%
 
-17515.9%
 
2020-10-29T22:43:06.789652image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:06.894127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:10.972913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length1
Mean length1.159235669
Min length1

SpatIL
Real number (ℝ)

HIGH CORRELATION

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.152866242
Minimum-1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:43:11.076371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q13
median4
Q35
95-th percentile5
Maximum5
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.184565603
Coefficient of variation (CV)0.6928824236
Kurtosis-0.2378130479
Mean3.152866242
Median Absolute Deviation (MAD)1
Skewness-1.182645461
Sum1485
Variance4.772326874
MonotocityNot monotonic
2020-10-29T22:43:11.168687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
420944.4%
 
513127.8%
 
-19319.7%
 
2214.5%
 
3143.0%
 
130.6%
 
ValueCountFrequency (%) 
-19319.7%
 
130.6%
 
2214.5%
 
3143.0%
 
420944.4%
 
ValueCountFrequency (%) 
513127.8%
 
420944.4%
 
3143.0%
 
2214.5%
 
130.6%
 

TLCar
Real number (ℝ≥0)

Distinct359
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1502.046709
Minimum1001
Maximum1996
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:43:11.293009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1041.5
Q11254.5
median1511
Q31751
95-th percentile1945.5
Maximum1996
Range995
Interquartile range (IQR)496.5

Descriptive statistics

Standard deviation287.635744
Coefficient of variation (CV)0.1914958718
Kurtosis-1.204413812
Mean1502.046709
Median Absolute Deviation (MAD)251
Skewness0.006558741966
Sum707464
Variance82734.32122
MonotocityNot monotonic
2020-10-29T22:43:11.441151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
155240.8%
 
117940.8%
 
188140.8%
 
145140.8%
 
117130.6%
 
118430.6%
 
121530.6%
 
140330.6%
 
156330.6%
 
162830.6%
 
Other values (349)43792.8%
 
ValueCountFrequency (%) 
100110.2%
 
100320.4%
 
100610.2%
 
101410.2%
 
101510.2%
 
ValueCountFrequency (%) 
199610.2%
 
199210.2%
 
199110.2%
 
198810.2%
 
198510.2%
 

TLHGV
Real number (ℝ≥0)

Distinct294
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean747.0169851
Minimum501
Maximum998
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:43:11.591213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum501
5-th percentile531.5
Q1626
median749
Q3867.5
95-th percentile965.5
Maximum998
Range497
Interquartile range (IQR)241.5

Descriptive statistics

Standard deviation140.9321843
Coefficient of variation (CV)0.1886599463
Kurtosis-1.217056149
Mean747.0169851
Median Absolute Deviation (MAD)122
Skewness0.02108472638
Sum351845
Variance19861.88056
MonotocityNot monotonic
2020-10-29T22:43:11.745166image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
52251.1%
 
53451.1%
 
85540.8%
 
85740.8%
 
73340.8%
 
63140.8%
 
62640.8%
 
70240.8%
 
80440.8%
 
63940.8%
 
Other values (284)42991.1%
 
ValueCountFrequency (%) 
50120.4%
 
50610.2%
 
50710.2%
 
51110.2%
 
51310.2%
 
ValueCountFrequency (%) 
99810.2%
 
99710.2%
 
99110.2%
 
99010.2%
 
98930.6%
 

Strasse
Categorical

Distinct12
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
A3
167 
A9
134 
A99
34 
A73
29 
A96
26 
Other values (7)
81 
ValueCountFrequency (%) 
A316735.5%
 
A913428.5%
 
A99347.2%
 
A73296.2%
 
A96265.5%
 
A6245.1%
 
A7183.8%
 
A92153.2%
 
A94112.3%
 
A93102.1%
 
Other values (2)30.6%
 
2020-10-29T22:43:11.907159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.2%
2020-10-29T22:43:12.046059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length2.271762208
Min length2

Kat
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
7
237 
3
210 
2
 
21
1
 
3
ValueCountFrequency (%) 
723750.3%
 
321044.6%
 
2214.5%
 
130.6%
 
2020-10-29T22:43:12.162953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:12.238958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:18.653316image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Typ
Real number (ℝ≥0)

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.182590234
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:43:18.761069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median6
Q36
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.761465323
Coefficient of variation (CV)0.3398812647
Kurtosis1.092116449
Mean5.182590234
Median Absolute Deviation (MAD)0
Skewness-1.645017727
Sum2441
Variance3.102760085
MonotocityNot monotonic
2020-10-29T22:43:18.859201image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
635475.2%
 
15611.9%
 
3398.3%
 
7173.6%
 
551.1%
 
ValueCountFrequency (%) 
15611.9%
 
3398.3%
 
551.1%
 
635475.2%
 
7173.6%
 
ValueCountFrequency (%) 
7173.6%
 
635475.2%
 
551.1%
 
3398.3%
 
15611.9%
 

Betei
Real number (ℝ≥0)

Distinct8
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.225053079
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size3.7 KiB
2020-10-29T22:43:18.974867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile3.5
Maximum8
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7937848651
Coefficient of variation (CV)0.3567487323
Kurtosis14.96809288
Mean2.225053079
Median Absolute Deviation (MAD)0
Skewness2.728535288
Sum1048
Variance0.6300944121
MonotocityNot monotonic
2020-10-29T22:43:19.088718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
232569.0%
 
38317.6%
 
1398.3%
 
4194.0%
 
820.4%
 
710.2%
 
610.2%
 
510.2%
 
ValueCountFrequency (%) 
1398.3%
 
232569.0%
 
38317.6%
 
4194.0%
 
510.2%
 
ValueCountFrequency (%) 
820.4%
 
710.2%
 
610.2%
 
510.2%
 
4194.0%
 

UArt1
Real number (ℝ≥0)

ZEROS

Distinct9
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.123142251
Minimum0
Maximum9
Zeros13
Zeros (%)2.8%
Memory size3.7 KiB
2020-10-29T22:43:19.209580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile8
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.098052668
Coefficient of variation (CV)0.6717762113
Kurtosis1.892733031
Mean3.123142251
Median Absolute Deviation (MAD)1
Skewness1.634104194
Sum1471
Variance4.401824999
MonotocityNot monotonic
2020-10-29T22:43:19.313406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
220743.9%
 
314230.1%
 
5316.6%
 
8275.7%
 
1234.9%
 
9214.5%
 
0132.8%
 
761.3%
 
610.2%
 
ValueCountFrequency (%) 
0132.8%
 
1234.9%
 
220743.9%
 
314230.1%
 
5316.6%
 
ValueCountFrequency (%) 
9214.5%
 
8275.7%
 
761.3%
 
610.2%
 
5316.6%
 

UArt2
Real number (ℝ)

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.3609341826
Minimum-1
Maximum9
Zeros1
Zeros (%)0.2%
Memory size3.7 KiB
2020-10-29T22:43:19.423506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median-1
Q3-1
95-th percentile8
Maximum9
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.289960136
Coefficient of variation (CV)-6.344536611
Kurtosis11.09146085
Mean-0.3609341826
Median Absolute Deviation (MAD)0
Skewness3.548931105
Sum-170
Variance5.243917423
MonotocityNot monotonic
2020-10-29T22:43:19.522321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
-143291.7%
 
9183.8%
 
881.7%
 
381.7%
 
520.4%
 
120.4%
 
010.2%
 
ValueCountFrequency (%) 
-143291.7%
 
010.2%
 
120.4%
 
381.7%
 
520.4%
 
ValueCountFrequency (%) 
9183.8%
 
881.7%
 
520.4%
 
381.7%
 
120.4%
 

AUrs1
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.473460722
Minimum0
Maximum89
Zeros437
Zeros (%)92.8%
Memory size3.7 KiB
2020-10-29T22:43:19.623606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile73
Maximum89
Range89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19.70178835
Coefficient of variation (CV)3.599512147
Kurtosis9.388591378
Mean5.473460722
Median Absolute Deviation (MAD)0
Skewness3.353122558
Sum2578
Variance388.1604644
MonotocityNot monotonic
2020-10-29T22:43:19.717441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
043792.8%
 
73163.4%
 
7291.9%
 
8240.8%
 
8920.4%
 
8820.4%
 
8010.2%
 
ValueCountFrequency (%) 
043792.8%
 
7291.9%
 
73163.4%
 
8010.2%
 
8240.8%
 
ValueCountFrequency (%) 
8920.4%
 
8820.4%
 
8240.8%
 
8010.2%
 
73163.4%
 

AUrs2
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
0
469 
81
 
1
80
 
1
ValueCountFrequency (%) 
046999.6%
 
8110.2%
 
8010.2%
 
2020-10-29T22:43:19.836839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.4%
2020-10-29T22:43:19.921634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:21.210254image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length1
Mean length1.004246285
Min length1

AufHi
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
399 
3
58 
4
 
11
5
 
3
ValueCountFrequency (%) 
-139984.7%
 
35812.3%
 
4112.3%
 
530.6%
 
2020-10-29T22:43:21.329352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:21.421189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:26.218878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.847133758
Min length1

Alkoh
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
465 
1
 
6
ValueCountFrequency (%) 
-146598.7%
 
161.3%
 
2020-10-29T22:43:26.382177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:26.475949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:27.980435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.987261146
Min length1

Char1
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
447 
5
 
11
4
 
10
6
 
3
ValueCountFrequency (%) 
-144794.9%
 
5112.3%
 
4102.1%
 
630.6%
 
2020-10-29T22:43:28.118075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:28.199699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:31.040904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.949044586
Min length1

Char2
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
465 
6
 
6
ValueCountFrequency (%) 
-146598.7%
 
661.3%
 
2020-10-29T22:43:31.188159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:31.274834image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:31.371403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.987261146
Min length1

Bes1
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
328 
6
143 
ValueCountFrequency (%) 
-132869.6%
 
614330.4%
 
2020-10-29T22:43:33.229557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:35.972815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:40.184777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.696390658
Min length1

Bes2
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
471 
ValueCountFrequency (%) 
-1471100.0%
 
2020-10-29T22:43:43.340767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:48.164507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:49.711029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

Lich1
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
0
402 
2
49 
1
 
20
ValueCountFrequency (%) 
040285.4%
 
24910.4%
 
1204.2%
 
2020-10-29T22:43:49.837664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:49.932710image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:57.141777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Lich2
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
402 
4
67 
3
 
2
ValueCountFrequency (%) 
-140285.4%
 
46714.2%
 
320.4%
 
2020-10-29T22:43:57.283883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:43:57.388560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:43:58.857958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.853503185
Min length1

Zust1
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
0
372 
1
89 
2
 
9
-1
 
1
ValueCountFrequency (%) 
037279.0%
 
18918.9%
 
291.9%
 
-110.2%
 
2020-10-29T22:43:59.008179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.2%
2020-10-29T22:43:59.107565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:44:03.192207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length1
Mean length1.002123142
Min length1

Zust2
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
467 
2
 
4
ValueCountFrequency (%) 
-146799.2%
 
240.8%
 
2020-10-29T22:44:03.323407image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:44:03.398195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:44:06.289450image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.991507431
Min length1

Fstf
Categorical

MISSING

Distinct6
Distinct (%)1.3%
Missing25
Missing (%)5.3%
Memory size3.7 KiB
2
216 
1
139 
3
71 
4
 
13
S
 
6
ValueCountFrequency (%) 
221645.9%
 
113929.5%
 
37115.1%
 
4132.8%
 
S61.3%
 
510.2%
 
(Missing)255.3%
 
2020-10-29T22:44:06.423630image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.2%
2020-10-29T22:44:06.510000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:44:13.661927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.106157113
Min length1

WoTag
Categorical

Distinct8
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Fr
97 
Do
85 
Mi
73 
Mo
67 
Di
62 
Other values (3)
87 
ValueCountFrequency (%) 
Fr9720.6%
 
Do8518.0%
 
Mi7315.5%
 
Mo6714.2%
 
Di6213.2%
 
Sa439.1%
 
So418.7%
 
30.6%
 
2020-10-29T22:44:13.800835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:44:13.894124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:44:23.813784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.987261146
Min length0

FeiTag
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
-1
461 
1
 
10
ValueCountFrequency (%) 
-146197.9%
 
1102.1%
 
2020-10-29T22:44:23.964529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:44:24.043176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:44:26.845381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length1.978768577
Min length1

Month
Categorical

Distinct12
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Jul
81 
Aug
54 
Sep
49 
Oct
44 
Nov
39 
Other values (7)
204 
ValueCountFrequency (%) 
Jul8117.2%
 
Aug5411.5%
 
Sep4910.4%
 
Oct449.3%
 
Nov398.3%
 
Mar367.6%
 
Apr337.0%
 
Dec337.0%
 
May316.6%
 
Jun316.6%
 
Other values (2)408.5%
 
2020-10-29T22:44:26.975803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-10-29T22:44:27.103127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Interactions

2020-10-29T22:41:50.997042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:51.565020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:52.178808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:52.942246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:53.514526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:54.040096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:54.554493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:55.072033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:55.602753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:56.203549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:56.803081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:57.387872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:57.987673image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:58.562702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:59.118071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:41:59.731665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:01.477237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:01.504475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:01.663249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:01.827660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:01.986311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:05.174399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:05.340028image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:05.515690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:05.678369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:06.397487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:06.559930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:06.707835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:06.873349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:07.042738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:07.196469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:07.341913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:08.106251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:08.132788image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:08.294542image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:08.454355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:08.607154image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:08.936705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:09.091998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:09.257777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:09.413926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:09.574840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:09.732330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:09.888287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:10.047216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:10.210150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:10.360868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:10.506736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:11.264908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:11.286477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:11.426743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:11.577186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:11.716770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:11.872887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.016335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.174140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.318048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.467943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.614704image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.759332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:12.906830image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:13.058906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:13.199872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:13.340766image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.105726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.131581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.299680image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.466376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.625700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.798272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:14.961975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:15.305500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:15.467638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:15.632506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:15.793253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:15.957309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:16.124917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:16.295527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:16.450876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:16.601852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:17.368353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:17.394533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:17.553164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:17.709264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:17.857519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.020448image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.170624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.335127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.489731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.645233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.795677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:18.946204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:19.093923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:19.243121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:19.390506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:19.535713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:20.304122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:20.329546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:20.505317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:20.679985image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:20.844877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:21.023324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:21.188992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:21.368439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:21.706269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:21.877750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:22.047545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:22.217490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:22.389236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:22.566091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:22.730014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:22.893796image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:23.667452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:23.693312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:23.850600image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.009454image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.157964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.314367image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.442638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.617306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.768249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:24.923659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:25.072908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:25.223797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:25.378701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:25.539977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:25.683245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:25.828294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:26.602611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:26.628020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:26.790172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:26.946438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:27.098031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:27.254070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:27.410705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:27.580941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:27.739469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:28.062882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:28.221161image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:28.379070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:28.539684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:28.704561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:28.856614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:29.008763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:29.768180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:29.794270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:29.951300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:30.107536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:30.256113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:30.431197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:30.583145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:30.750486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:30.901459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.057514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.208706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.359806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.514369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.665555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.814080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:31.959897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:32.710503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:32.736729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:32.893486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.048514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.196253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.358696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.510353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.675817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.830884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:33.987304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:34.135656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:34.453738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:34.608802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:34.761869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:34.902453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:35.048623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:35.808197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:35.834700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:35.999951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:36.159866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:36.314767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:36.482241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:36.638823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:36.808964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:36.966589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.128993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.286175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.414913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.543921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.664531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.786049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:37.909737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:38.522345image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:38.543563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:38.679352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:38.810918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:38.940508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.077022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.208054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.350953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.481124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.615505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.745446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:39.876646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:40.160486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:40.302050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:40.428355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:40.557017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.162197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.183323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.306236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.424378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.537697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.654821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.788966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:41.949423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.089877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.223299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.353430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.482357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.614737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.750659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:42.875451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:43.015480image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:43.792497image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:43.820873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:43.985405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:44.147997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:44.310613image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:44.495596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:44.663948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:44.831684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:44.984488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:45.141813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:45.304823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:45.447173image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:45.590200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:45.724844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:45.846616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:46.139179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:46.816727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:46.839756image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:46.972917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.106663image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.236337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.373738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.517185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.672194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.805137image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:47.953314image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:48.098807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:48.244163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:48.394074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:48.549010image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:48.681371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:48.817301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-10-29T22:44:27.826850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-10-29T22:44:28.516979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-10-29T22:44:29.203415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-10-29T22:44:29.899116image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-10-29T22:44:29.996038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-10-29T22:42:50.004983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:51.008879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-10-29T22:42:51.689668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

df_indexTempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTempGLSpatGLTempILSpatILTLCarTLHGVStrasseKatTypBeteiUArt1UArt2AUrs1AUrs2AufHiAlkohChar1Char2Bes1Bes2Lich1Lich2Zust1Zust2FstfWoTagFeiTagMonth
0216289139257212005032441293804A336529003-1-1-1-1-10-11-12Mi-1Jan
15452074833057004232551044780A63632-100-11-1-1-1-10-10-11Mi-1Jan
281385564153142004232441803985A97123-100-1-1-1-1-1-1240-11Fr-1Jan
391056199412555011222335-11657905A93632-100-1-1-1-1-1-1241-14Fr-1Jan
410873225314134387001332551674752A37119-17303-1-1-1-1-10-11-13Sa-1Jan
513189762798710911003932441247531A93123-1720-1-15-1-1-10-1121Sa-1Jan
6199744612207904952-141925812A77118-17203-1-1-1-1-1242-12So1Jan
727452947392782212106153-1-11015984A67321-100-1-1-1-1-1-10-1122Mi-1Jan
831905661443235005132551881598A676208003-1-1-1-1-10-11-12Do-1Jan
9331268328962010006532551659895A937623-100-1-1-1-1-1-1242-12Do-1Jan

Last rows

df_indexTempMaxTempAvgSpatMaxSpatAvgTempDistSpatDistCoverageTempGLSpatGLTempILSpatILTLCarTLHGVStrasseKatTypBeteiUArt1UArt2AUrs1AUrs2AufHiAlkohChar1Char2Bes1Bes2Lich1Lich2Zust1Zust2FstfWoTagFeiTagMonth
4611817781967411718002332441285899A943622-100-1-1-1-1-1-1140-13Di-1Dec
462182415037147556121004132551913774A33642-100-1-1-1-1-1-1241-11-1Dec
4631827181124171564004832441097663A97118-1003-156-1-1240-13Do-1Dec
4641829792263370468388002232441421655A37622-100-1-1-1-1-1-1241-12-1Dec
4651830696199239666775002732551854982A33632-100-1-1-1-16-1241-12Fr-1Dec
4661833729275369118020002132551782567A33632-100-1-1-1-1-1-10-10-12Sa-1Dec
4671834300160156398285005232441076855A33681-100-1-1-1-1-1-10-10-12Sa-1Dec
4681835300160156398285005232551076855A33622-100-1-16-1-1-10-10-12Sa-1Dec
46918378724170693715031021335-11017969A33622-100-1-1-1-1-1-10-10-12Sa-1Dec
47018521234685193828004232441928876A93621-100-1-1-1-1-1-10-10-11Do1Dec